Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R PDF Download

Author: Joseph F. Hair Jr.
Publisher: Springer Nature
ISBN: 3030805190
Category : Business & Economics
Languages : en
Pages : 208

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Book Description
Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

Author: Juan J. Dolado
Publisher: Emerald Group Publishing
ISBN: 1803828331
Category : Business & Economics
Languages : en
Pages : 188

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Book Description
Both parts of Volume 44 of Advances in Econometrics pay tribute to Fabio Canova for his major contributions to economics over the last four decades.

Author: L. Andries van der Ark
Publisher: Springer Nature
ISBN: 303110370X
Category : Education
Languages : en
Pages : 461

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Book Description
This book 'Essays on Contemporary Psychometrics' provides an overview of contemporary psychometrics, the science devoted to the advancement of quantitative measurement practices in psychology, education and the social sciences. The volume consists of four parts, each having several chapters on cutting-edge work in the field. Part I, General Perspectives on Psychometrics, includes expert views on topics such as psychological models vs. measurement models, using tests in decision making, artificial intelligence, and psychometric network models. Part II, Factor Analysis and Classical Test Theory, the type of psychometrics that is still used most often in the social and behavioral sciences, includes state-of-the-art contributions on test-score reliability, change-score reliability, handling missing data in principal component analysis, test equating, and conditional standard errors of measurement. Part III, Item Response Theory, the leading form of psychometrics in modern educational measurement, includes discussions of sampling from many conditional distributions, transparent score reporting, nonparametric item response theory, and targeted testing. Part IV, New Psychometrics, discusses recently developed ideas beyond classical test theory and item response theory, including topics related to computer adaptive testing, response-time modelling, validity indices, diagnostic classification models, and the sparse latent class model for ordinal measurements. Together, these four parts provide an overview of the current state-of-the-art in psychometrics in educational measurement. They are a valuable source of information for graduate students who (intend to) study psychometrics and need an overview of the field, and for researchers interested in the current developments in the field. Chapters [3], [5], [8], [16] and [19] are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Author: Sarah Depaoli
Publisher: Guilford Publications
ISBN: 1462547745
Category : Social Science
Languages : en
Pages : 549

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Book Description
This book offers researchers a systematic and accessible introduction to using a Bayesian framework in structural equation modeling (SEM). Stand-alone chapters on each SEM model clearly explain the Bayesian form of the model and walk the reader through implementation. Engaging worked-through examples from diverse social science subfields illustrate the various modeling techniques, highlighting statistical or estimation problems that are likely to arise and describing potential solutions. For each model, instructions are provided for writing up findings for publication, including annotated sample data analysis plans and results sections. Other user-friendly features in every chapter include "Major Take-Home Points," notation glossaries, annotated suggestions for further reading, and sample code in both Mplus and R. The companion website (www.guilford.com/depaoli-materials) supplies data sets; annotated code for implementation in both Mplus and R, so that users can work within their preferred platform; and output for all of the book’s examples.

Author: Niels Blunch
Publisher: SAGE
ISBN: 1446271846
Category : Reference
Languages : en
Pages : 314

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Book Description
This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS′ graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this second edition is the ideal guide for those new to the field. The book includes: Learning objectives, key concepts and questions for further discussion in each chapter. Helpful diagrams and screenshots to expand on concepts covered in the texts. Real life examples from a variety of disciplines to show how SEM is applied in real research contexts. Exercises for each chapter on an accompanying companion website. A new glossary. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline. Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark

Author: Rick H. Hoyle
Publisher: SAGE
ISBN: 9780803953185
Category : Psychology
Languages : en
Pages : 316

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Book Description
Reviews some of the major issues facing researchers who wish to use structural equation modeling. This title includes individual chapters that present developments on specification, estimation and testing, statistical power, software comparisons and analyzing multitrait/multimethod data.

Author: Mike W.-L. Cheung
Publisher: John Wiley & Sons
ISBN: 1119993431
Category : Mathematics
Languages : en
Pages : 402

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Book Description
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

Author: J. Christopher Westland
Publisher: Springer
ISBN: 3319165070
Category : Technology & Engineering
Languages : en
Pages : 184

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Book Description
This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow importance in the near future. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained and methods are presented for extending their power, including guidelines for data preparation, sample size calculation and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.

Author: Alexander Chudik
Publisher: Emerald Group Publishing
ISBN: 180262063X
Category : Business & Economics
Languages : en
Pages : 316

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Book Description
The collection of chapters in Volume 43 Part A of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.

Author: J. Christopher Westland
Publisher: Springer
ISBN: 3030125084
Category : Technology & Engineering
Languages : en
Pages : 155

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Book Description
This new edition surveys the full range of available structural equation modeling (SEM) methodologies. The book has been updated throughout to reflect the arrival of new software packages, which have made analysis much easier than in the past. Applications in a broad range of disciplines are discussed, particularly in the social sciences where many key concepts are not directly observable. This book presents SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that are growing in importance. SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained and methods are presented for extending their power, including guidelines for data preparation, sample size calculation and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.